Skip To Main Content
epam-logo-black.svgepam-logo-black.svg
backBack to Search

Lead Data Integration Engineer

Remote in Republic of Lithuania
Data Integration& 7 others
Looking for something else?

Find a vacancy that works for you. Send us your CV to receive a personalized offer.

Find me a job

We are looking for an experienced Lead Data Integration Engineer to join our team. The ideal candidate has at least 5 years of experience in data management, storage, modeling, analytics, migration, and database design. As a Tech Lead/Team Lead, you will design and implement innovative data integration solutions, contribute to cloud solution architecture, and lead a high-performing team to ensure best practices are followed. Your deep expertise in cloud environments, data warehousing solutions, and data security will help drive the success of our projects.

Responsibilities
  • Lead a team of engineers, providing technical leadership and mentorship
  • Design and implement data integration solutions, model databases, and build scalable data platforms
  • Work with classic Data technologies and tools (Databases, ETL/ELT, MDM tools, BI platforms) as well as implement modern Cloud or Hybrid data solutions
  • Contribute to Cloud Solution Architecture, select the right toolset, and serve as a role model for the team
  • Collaborate with product and engineering teams to define technical requirements, evaluate new features, and drive architectural decisions
  • Build partnerships with architects and key stakeholders within the organization
  • Perform detailed analysis of business problems and technical environments to design high-quality solutions
  • Participate in code reviews and testing to ensure adherence to best practices
  • Foster a high-performance engineering culture, oversee team members, and provide technical guidance
  • Write and maintain project documentation, including high-quality technical documentation and use cases
Requirements
  • 5+ years of experience in Data Management, Storage, Analytics, Migration, and Database Design
  • Proven ability to lead technical teams and mentor engineers
  • Expert knowledge of Cloud environments (AWS, Azure, GCP) and experience with multiple cloud providers
  • Deep expertise in cloud data warehousing solutions (Redshift, Azure Synapse Analytics, Google BigQuery, Snowflake, etc.)
  • Experience designing and implementing Data Integration, Data Analytics & Visualization, and Cloud Migration solutions
  • Expertise in Data Integration tools (Azure Data Factory, AWS Glue, GCP Dataflow, Talend, Informatica, Apache NiFi, KNIME, SSIS, etc.)
  • Strong understanding of Relational Databases (MS SQL Server, Oracle, MySQL, PostgreSQL) and the ability to articulate the pros and cons of different solutions
  • Production coding experience in one of the data-oriented programming languages (SQL, Python, SparkSQL, PySpark, R, Bash, Scala)
  • Advanced knowledge of Data Security (Row-level security, auditing, etc.)
  • Experience with data modeling, including OLAP, OLTP, ETL, DWH, Data Lake, Delta Lake, and Data Mesh methodologies
  • Strong knowledge of integration patterns, CDC methods, micro-batching, and delta extracts
  • General understanding of Housekeeping processes (logging, monitoring, exception management, archiving, retention policies, hot/cold data)
  • Deep understanding of Data Lineage, Metadata Management, and Data Traceability concepts
  • Ability to create high-quality design documentation and maintain audit records
  • Compliance awareness (PI, GDPR, HIPAA)
  • Experience in direct customer communication and ability to present technical solutions effectively
  • Experience across various business domains
  • English proficiency for professional communication
Technologies
  • Cloud Platforms (AWS, Azure, GCP): Storage, Compute, Networking, Identity & Security, Data Warehousing (Redshift, Snowflake, BigQuery, Azure Synapse)
  • Data Integration Tools (Azure Data Factory, AWS Glue, GCP Dataflow, Talend, Informatica, Apache NiFi, KNIME, SSIS, etc.)
  • Programming Languages: SQL, Python, SparkSQL, PySpark, R, Bash, Scala
  • Relational Databases (MS SQL Server, Oracle, MySQL, PostgreSQL)
  • Dataflow orchestration, replication, and data preparation tools
  • Version Control Systems (Git, SVN)
  • Testing: Component, Integration Testing, and Data Reconciliation